Civil Engineer

If you are a civil engineer who thrives on technical precision, applied problem-solving, and infrastructure-focused reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex engineering concepts. We are looking for civil engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Civil Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs.

Your profile

• 4+ years of professional civil engineering experience, with significant hands-on work in infrastructure design, structural analysis, geotechnical engineering, transportation engineering, water resources, environmental engineering, construction management, or a closely related civil engineering specialty.
• Deep knowledge of civil engineering fundamentals, including statics, mechanics of materials, soil mechanics, hydraulics, materials behavior, load paths, construction methods, and infrastructure systems.
• Bachelor’s degree in Civil Engineering or a closely related engineering discipline required; Master’s degree, PhD, PE licensure, or equivalent advanced professional credentials strongly preferred.
• Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.

Key responsibilities

• Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across civil engineering topics.
• Challenge advanced language models with realistic civil engineering scenarios, calculations, design questions, and code-informed reasoning tasks.
• Review and refine AI-generated prompts, model responses, explanations, and step-by-step engineering solutions.
• Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, or incomplete reasoning.
• Assess model performance on topics such as structural loads, soil behavior, slope stability, drainage design, pavement systems, reinforced concrete, steel design, and construction sequencing.
• Help shape AI communication standards for technical civil engineering content, including how models explain assumptions, limitations, calculations, and professional judgment.
• Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication.